Author:
Tsume Yasuhiro,Ashworth Lee,Bermejo Marival,Cheng Joan,Cicale Vincent,Dressman Jennifer,Fushimi Masahiro,Gonzalez-Alvarez Isabel,Guo Yiwang,Jankovsky Corinne,Lu Xujin,Matsui Kazuki,Patel Sanjaykumar,Sanderson Natalie,Sun Changquan Calvin,Thakral Naveen K.,Yamane Miki,Zöller Laurin
Abstract
AbstractAssessing in vivo performance to inform formulation selection and development decisions is an important aspect of drug development. Biopredictive dissolution methodologies for oral dosage forms have been developed to understand in vivo performance, assist in formulation development/optimization, and forecast the outcome of bioequivalence studies by combining them with simulation tools to predict plasma profiles in humans. However, unlike compendial dissolution methodologies, the various biopredictive methodologies have not yet been harmonized or standardized. This manuscript presents the initial phases of an effort to develop best practices and move toward standardization of the biopredictive methodologies through the Product Quality Research Institute (PQRI, https://pqri.org) entitled “The standardization of in vitro predictive dissolution methodologies and in silico bioequivalence study Working Group.” This Working Group (WG) is comprised of participants from 10 pharmaceutical companies and academic institutes. The project will be accomplished in a total of five phases including assessing the performance of dissolution protocols designed by the individual WG members, and then building “best practice” protocols based on the initial dissolution profiles. After refining the “best practice” protocols to produce equivalent dissolution profiles, those will be combined with physiologically based biopharmaceutics models (PBBM) to predict plasma profiles. In this manuscript, the first two of the five phases are reported, namely generating biopredictive dissolution profiles for ibuprofen and dipyridamole and using those dissolution profiles with PBBM to match the clinical plasma profiles. Key experimental parameters are identified, and this knowledge will be applied to build the “best practice” protocol in the next phase.
Graphical Abstract
Publisher
Springer Science and Business Media LLC
Cited by
2 articles.
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